Yearly Traffic Safety Analysis

402 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In Plymouth County, total crashes decreased from 518 in 2019 to 402 in 2020, a 22.4% reduction. Despite the overall drop in collisions, the number of fatalities rose sharply from 2 to 9, and the count of fatal crashes increased from 2 to 8 during the same period.

402

▼ -22.4%was 518

Total Crash Events

9

▲ 350.0%was 2

Persons Killed

149

▼ -1.3%was 151

Persons Injured

8

▲ 300.0%was 2

Fatal Crash Events

Note: "Persons Killed" (9) counts individual fatalities across all crash events. "Fatal" in the severity table below (8) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Year-over-year, Plymouth County saw a significant downward trend in total traffic collisions, with a 22.4% decrease from 518 crashes in 2019 to 402 in 2020. However, the outcomes of these crashes became more severe, as total injuries remained nearly flat, decreasing from 151 to 149, while fatalities increased from 2 to 9.

Vulnerable Road User Casualties

9

Motorists Killed

Prior: 2↑350.0%

149

Motorists Injured

Prior: 147↑1.4%

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes in Plymouth County shifted between 2019 and 2020. The peak day for collisions moved from Monday (90 crashes) in the prior period to Friday (72 crashes) in the current period. While the 4 p.m. hour remained the busiest time of day in both years, the number of crashes during that hour decreased from 38 to 29. Monthly crash distribution also varied, with January experiencing an increase from 39 to 53 crashes year-over-year, while November saw a decrease from 57 to 36.

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes declined, the severity of collisions in Plymouth County increased from 2019 to 2020. The number of fatal crashes rose from 2 to 8, and the fatal crash rate increased from 0.4% to 2.0% of all crashes. The proportion of crashes resulting in an injury (serious, minor, or possible) saw a slight increase from 24.3% to 26.6%. Correspondingly, the share of crashes with no reported injuries decreased from 75.3% in 2019 to 71.4% in 2020.

Severity is per crash event (most severe injury). 8 fatal crash events resulted in 9 persons killed.

Outcome by Severity (Crash Events)

Fatal8fatal crashes2%
↑300.0%prior 2
Serious Injury12serious injury crashes3%
↓-20.0%prior 15
Minor Injury57minor injury crashes14.2%
↓-12.3%prior 65
Possible Injury38possible injury crashes9.5%
↓-17.4%prior 46
No Injury287no injury crashes71.4%
↓-26.4%prior 390

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an 'Animal' remained the leading contributing factor in both periods, though the count of such crashes decreased by 35.3% from 136 in 2019 to 88 in 2020. 'Lost Control' was the second-most cited factor in both years, with its count declining slightly from 41 to 37. Crashes attributed to 'Failure to yield from a stop sign' saw a notable drop in count from 33 to 19. Conversely, crashes involving 'Ran Stop Sign' increased in count from 13 to 17.

Officer-Reported Primary Contributing Cause

Animal88 (21.9%)↓-35.3%prior 136
Lost Control37 (9.2%)↓-9.8%prior 41
Driving too fast for conditions30 (7.5%)↓-3.2%prior 31
Followed too close25 (6.2%)↓-7.4%prior 27
Ran off road - straight19 (4.7%)↑11.8%prior 17
Ran off road - left19 (4.7%)→0.0%prior 19
FTYROW: From stop sign19 (4.7%)↓-42.4%prior 33
Ran Stop Sign17 (4.2%)↑30.8%prior 13
FTYROW: At uncontrolled intersection15 (3.7%)↓-21.1%prior 19
Other (explain in narrative): Other14 (3.5%)↓-46.2%prior 26

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring in clear weather and on dry roads increased from 2019 to 2020. Crashes in clear weather constituted 55.2% of the total in 2020, up from a 46.9% share in the prior year, while collisions on dry surfaces rose from a 51.2% share to 58.7%. Correspondingly, crashes during rain (25 to 6) and on wet roads (51 to 14) saw a substantial decrease in count. The share of crashes happening in daylight also increased from 51.2% to 57.2%.

Weather

Clear222 (69.2%)
↓-8.6%prior 243
Cloudy52 (16.2%)
↓-42.9%prior 91
Snow14 (4.4%)
→0.0%prior 14
Freezing rain/drizzle12 (3.7%)
↓-36.8%prior 19
Blowing Snow7 (2.2%)
Rain6 (1.9%)
↓-76.0%prior 25
Severe Winds4 (1.2%)
Other (explain in narrative)2 (0.6%)
Fog, smoke, smog2 (0.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Weather condition at time of crash

Lighting

Daylight230 (71.4%)
↓-13.2%prior 265
Dark - roadway not lighted61 (18.9%)
↓-22.8%prior 79
Dark - roadway lighted20 (6.2%)
↓-39.4%prior 33
Dawn7 (2.2%)
↓-22.2%prior 9
Dusk4 (1.2%)
↓-69.2%prior 13

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Lighting condition field

Road Surface

Dry236 (73.1%)
↓-10.9%prior 265
Ice/frost35 (10.8%)
↓-7.9%prior 38
Snow22 (6.8%)
↓-15.4%prior 26
Wet14 (4.3%)
↓-72.5%prior 51
Gravel7 (2.2%)
↓-46.2%prior 13
Mud, dirt4 (1.2%)
Other (explain in narrative)2 (0.6%)
Slush2 (0.6%)
↓-60.0%prior 5
Oil1 (0.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Road surface condition field

Vehicles & Demographics

Ford and Chevrolet remained the top two vehicle makes involved in crashes in both 2019 and 2020, although the count for both decreased year-over-year; Fords involved in crashes fell from 149 to 115, and Chevrolets dropped from a combined 172 to 105. The age distribution of persons involved in crashes showed a similar profile across both periods. For example, the 16-20 age group represented 13.4% of involved persons with a known age in 2020, nearly unchanged from their 13.0% share in 2019.

Top Vehicle Makes (598 vehicles)

1
FORD115 (19.2%)
↓-22.8%prior 149
2
CHEV64 (10.7%)
↓-45.8%prior 118
3
CHEVROLET41 (6.9%)
↓-24.1%prior 54
4
GMC26 (4.3%)
↓-38.1%prior 42
5
BUIC24 (4%)
↑41.2%prior 17
6
DODGE23 (3.8%)
↑4.5%prior 22
7
PETERBILT22 (3.7%)
↑46.7%prior 15
8
DODG22 (3.7%)
↓-31.3%prior 32
9
KIA19 (3.2%)
→0.0%prior 19
10
HOND19 (3.2%)
↑11.8%prior 17

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Vehicle unit records

39 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (570 persons with recorded sex)

Male368 (64.6%)
↓-17.3%prior 445
Female202 (35.4%)
↓-28.4%prior 282

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Person-level records linked to crash events

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Iowa Crash Data, accessed programmatically via the ArcGIS Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

  • Access method: ArcGIS Open Data API (SoQL queries)
  • Data format: Structured JSON via REST API
  • Record types queried: Crash events, person records, and vehicle unit records
  • Date filter applied: 2020-01-01 through 2020-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2020-01-01 through 2020-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 402
  • Total persons involved: 857
  • Total vehicles involved: 598

Analytical Methodology

  • Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
  • Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
  • Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
  • Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
  • Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
  • Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
  • AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.

Limitations & Disclaimers

  • Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
  • Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
  • Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
  • AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
  • Percentages are calculated from reported data and are subject to rounding.

Non-Affiliation Disclosure

This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.

Data License

The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.

Corrections & Feedback

If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "iowa, IA Crash Intelligence Report: 2020." Published September 9, 2026. Reporting period: 2020-01-01 to 2020-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2020-annual-report

About the Publisher

ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.

Questions about this report's data or methodology: data@injuria.ai

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